RoboTwin 2.0 Dataset
Bimanual simulation data generation and evaluation
A configurable dual-arm data generator and benchmark with strong domain randomization, pre-collected trajectories, and LeRobot integration.
Bimanual VLA post-training
This entry covers a generator, released trajectories, and benchmark; keep those artifacts distinct in the future release schema.
Inspect schema and run a bounded sample audit before committing to the full release.
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has visual observations plus geometry, calibration, depth, or reconstruction cues.
fit 82 · confidence 55
Contains observation, intent, action/state, and feedback-like supervision.
fit 88 · confidence 55
Verified facts and provenance
Claims, metadata verification, and sample verification are shown separately.
Unknown — no machine-readable schema facts have been captured.
Unknown — metadata conclusions do not prove sample coverage, alignment, or file integrity.
Declared loop signal coverage
Signals inferred from official metadata; Data pipeline verification is still pending.
Observation / ego video
video · depth
Action / hand pose / robot state
actions · robot state · Trajectory data
Gaze / attention
No decision-grade evidence captured yet.
Language intent / task phase
task phase
Feedback / correction / failure
Bimanual simulation data generation and evaluation
Sim-real pairing
depth · sim-real · Simulation assets · Bimanual simulation data generation and evaluation
License / format / access
Open · MIT (code; verify generated asset terms) · LeRobot v3.0 · Simulation assets
Model and task fit · OpenBot inference
Has observation, action/state proxy, and task or language context.
fit 85 · confidence 55
Has visual observations plus geometry, calibration, depth, or reconstruction cues.
fit 82 · confidence 55
Contains observation, intent, action/state, and feedback-like supervision.
fit 88 · confidence 55
Has failure/evaluation-style labels with action or manipulation context.
fit 82 · confidence 55
Good tasks
Blockers and unresolved evidence
- Gaze / attentionunknownNot enough evidence to classify this signal. Verify metadata or a bounded sample.
Raw dataset signals
OpenBot fit
- Bimanual VLA post-training
- Domain randomization
- Policy benchmark
Related models and papers
Model references linked to similar loop signals.
Integration notes
- This entry covers a generator, released trajectories, and benchmark; keep those artifacts distinct in the future release schema.